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MSc Artificial Intelligence and Digital Health

University of Westminster — London, United Kingdom

MSc Artificial Intelligence and Digital Health is a postgraduate Data Science & AI course at University of Westminster, London, United Kingdom. It takes 1 year, costs £18,685 per year and starts in September.

Postgraduate · 1 year · Full-time · Data Science & AI · £18,685 per year

Intakes: September

AI is everywhere. If you want to future-proof your career, a solid understanding of AI is required, including in healthcare. Our MSc in Artificial Intelligence and Digital Health offers a comprehensive and interdisciplinary approach which will equip you with this knowledge and prepare you for the dynamic field of digital health. Whether your background is in life sciences or computing, we’ll provide you with the necessary tools, methods, and experiences in using AI to analyse complex datasets. These datasets will be drawn from various aspects of healthcare, including diagnosis, disease prevention and wellness promotion. Top reasons to study this course (from the course page): - Be at the forefront – the UK is pioneering advancements in AI and Healthcare, with schemes such as the UK Biobank and Genomics England leading the way, making London the perfect place to study this subject, as it’s a hub for global AI companies and institutions such as Google DeepMind and The Alan Turing Institute. - Interdisciplinary focus – this course provides a unique opportunity to study at the intersection between healthcare, AI and big data and is suitable for students from either a bioscience or computing background - Industry relevant skills – our connections to external advisors and organisations including AstraZeneca, GSK and BenevolentAI allow you to gain the practical skills that are in demand in industry - Exciting research opportunities – our academic team are engaged in cutting-edge research, giving you the opportunity to collaborate in projects including those led by our Health Data Science research group - Aligned with UN Sustainable Development Goals – we focus on global healthcare challenges that impact the entire world, including underrepresented populations, preparing you to improve global healthcare access Campus: Cavendish, Central London Duration: 1 year Start dates: Full-time - September 2027 International tuition fee: £18,685 (Price per academic year). The university states annual fees stay the same throughout your studies. Careers (from the course page): Whether your background is in biosciences or computing, this course will equip you with the specialist knowledge and skills to succeed in the field of digital health and leverage AI to improve patient care. Not only will you gain the technical skills to do this, but you’ll also learn how to apply these skills in a commercial setting, opening up a range of career possibilities in a city like London, which is a hub for healthcare innovation, technology, and research. Graduate employers named on the course page: Graduates from this course will be prepared to work in a range of areas, including:, NHS and other Healthcare providers, Public and governmental policy bodies, Small, Medium and Large Pharmaceutical and Biotechnology Companies., Pharma or big data-centred consultancy, Academic research and development laboratories. Source: University of Westminster course page.

Modules

• Biobanking for Data Science (Core)
• Introduction to Data Science (Core)
• Postgraduate Research Methods (Core)
• Data Mining and Machine Learning (Core)
• Postgraduate Project (Core)
• Big Data Theory and Practice (Option)
• Communicating Science (Option)
• Data Visualising and Dashboarding (Option)
• Science, Technology and Commercialisation (Option)
• Systems Biology (Option)
• Professional recognition (Option)

Careers

• AI researcher
• Data scientist
• Healthcare IT specialist
• Precision medicine consultant
• Researcher/PhD student
• Digital Health Strategist
• Clinical Informatics Specialist
• Bioinformatics Analyst
• AI Policy Analyst
• Genomic Data Scientist
• Digital Health Project Manager
• User Experience (UX) Designer for Digital Health
• Health Data Analyst
• Machine Learning Engineer in Healthcare